Coughing is a common symptom which may result in significant health care costs, medical consultations, and medication use. Proper diagnosis, monitoring, and management of coughs for an individual or population individuals may be of importance.
One conventional method for monitoring coughs includes self-reporting by the individual, which tends to be highly inaccurate. Other known methods for monitoring coughs include automatic cough detection systems which measure thoracic pressure changes in order to determine whether a cough has occurred and thus monitor the frequency of coughs. However, such thoracic pressure based systems tend to be very expensive and cumbersome, as the individual may be required to wear specialized pressure measuring equipment or clothing.
More recent developments in cough detection include certain advances in audio-based cough detection. However, known methods for audio-based detection of coughs generally expose private information about the individual to the person or entity monitoring or classifying the cough. For example, one currently known audio-based detection system is the Leicester Cough Monitor (LCM) system which uses a lapel microphone with a portable audio recorder. However, the LCM system is not only semi-autonomous as it requires human annotators to listen and discard false positives, but is also a poor performer when it comes to preserving audio privacy. The LCM methodology reveals not only speech but also inflections and prosody in the recorded audio. As such, conventional audio-based detection systems may be poorly adapted to offer both accuracy and privacy protection features. The examples described herein may address some or all of the shortcomings in the art, as well as provide additional benefits.